Longitudinal Peripheral Blood Lymphocyte Subsets Correlate with Decreased Disease Activity in Juvenile Dermatomyositis
Bibliographic record
Abstract
OBJECTIVE: To determine the clinical characteristics and subsets of peripheral blood lymphocytes (PBL), which correlate with decreased disease activity in patients with juvenile dermatomyositis (JDM). METHODS: Peripheral blood mononuclear cells from 24 patients with JDM were collected at Mayo Clinic Rochester between 2007 and 2011. These were analyzed using fluorescence-activated cell sorting and flow cytometry. Clinical disease activity was determined by visual analog scales (VAS) collected in 2 consecutive visits and correlated with PBL subsets. RESULTS: The change in CD3+CD69+ T cells correlated with the change in global VAS scores. The change in HLA-DR- CD11c+ myeloid dendritic cells also correlated with the change in extramuscular VAS scores. There were trends toward decreased levels of HLA-DR- CD11c+ cells with decreased muscle and global VAS scores, but these did not reach significance. The change in HLA-DR- CD123+ plasmacytoid dendritic cells negatively correlated with the change in muscle VAS scores. Although not statistically significant, decreased levels of CD3-CD16- CD56+ natural killer (NK) cells and HLA-DR- CD86+ myeloid dendritic cells, and increased levels of CD16+CD56- NK cells, correlated with decreased VAS scores. CONCLUSION: Changes in CD3+CD69+ T cells, HLA-DR- CD11c+ myeloid dendritic cells, and HLA-DR- CD123+ plasmacytoid dendritic cells are associated with improved clinical course in JDM and could be used as markers for disease activity, but findings need to be verified in a larger, independent cohort. Lack of significant differences among most of our PBL subsets suggests that lymphocyte phenotyping may be difficult to definitively correlate with disease activity in JDM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".